Sangrahaka: A Tool for Annotating and Querying Knowledge Graphs
원문 초록
In this work, we present a web-based annotation and querying tool Sangrahaka. It annotates entities and relationships from text corpora and constructs a knowledge graph (KG). The KG is queried using templatized natural language queries. The application is language and corpus agnostic, but can be tuned for special needs of a specific language or a corpus. A customized version of the framework has been used in two annotation tasks. The application is available for download and installation. Besides having a user-friendly interface, it is fast, supports customization, and is fault tolerant on both client and server side. The code is available at https://github.com/hrishikeshrt/sangrahaka and the presentation with a demo is available at https://youtu.be/nw9GFLVZMMo.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
Complex System Diagnostics Using a Knowledge Graph-Informed and Large Language Model-Enhanced Framework
RouteNator: A Router-Based Multi-Modal Architecture for Generating Synthetic Training Data for Function Calling LLMs
SQL-o1: Automatic Text-to-SQL Program Synthesis via Self-Reward Heuristic Search
Graph Collaborative Attention Network for Link Prediction in Knowledge Graphs
A Multi-Expert Structural-Semantic Hybrid Framework for Unveiling Historical Patterns in Temporal Knowledge Graphs
Learning Efficient and Generalizable Graph Retriever for Knowledge-Graph Question Answering
토론
이 논문과 연결된 포럼 글이 아직 없습니다.